Long-term Visual Tracking: Review and Experimental Comparison

doi:10.1007/s11633-022-1344-1

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > International Journal of Automation and Computing

	Long-term Visual Tracking: Review and Experimental Comparison
	Chang Liu 2
刊名	Machine Intelligence Research
	2022
卷号	19 期号:6 页码:512-530
关键词	Visual object tracking long-term tracking short-term tracking re-detection online update
ISSN号	2731-538X
DOI	10.1007/s11633-022-1344-1
英文摘要	As a fundamental task in computer vision, visual object tracking has received much attention in recent years. Most studies focus on short-term visual tracking which addresses shorter videos and always-visible targets. However, long-term visual tracking is much closer to practical applications with more complicated challenges. There exists a longer duration such as minute-level or even hour-level in the long-term tracking task, and the task also needs to handle more frequent target disappearance and reappearance. In this paper, we provide a thorough review of long-term tracking, summarizing long-term tracking algorithms from two perspectives: framework architectures and utilization of intermediate tracking results. Then we provide a detailed description of existing benchmarks and corresponding evaluation protocols. Furthermore, we conduct extensive experiments and analyse the performance of trackers on six benchmarks: VOTLT2018, VOTLT2019 (2020/2021), OxUvA, LaSOT, TLP and the long-term subset of VTUAV-V. Finally, we dis- cuss the future prospects from multiple perspectives, including algorithm design and benchmark construction. To our knowledge, this is the first comprehensive survey f
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/50570]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	1.Dalian Minzu University, Dalian 116600, China 2.School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China
推荐引用方式 GB/T 7714	Chang Liu. Long-term Visual Tracking: Review and Experimental Comparison[J]. Machine Intelligence Research,2022,19(6):512-530.
APA	Chang Liu.(2022).Long-term Visual Tracking: Review and Experimental Comparison.Machine Intelligence Research,19(6),512-530.
MLA	Chang Liu."Long-term Visual Tracking: Review and Experimental Comparison".Machine Intelligence Research 19.6(2022):512-530.